# Inkeep vs OpenAI Platform

Inkeep records 28,786 monthly visits with -5.1% month-over-month growth and Contact for Pricing pricing. OpenAI Platform records 234,678,639 monthly visits with -9.6% growth and Paid pricing.

| Metric | [Inkeep](https://openaitools.app/tool/inkeep) | [OpenAI Platform](https://openaitools.app/tool/openai) |
| :--- | :--- | :--- |
| Website URL | https://inkeep.com | https://openai.com |
| Categories | AI Customer Service, AI Chatbot, AI Copilot, AI Agent | AI Models, AI API, Large Language Models (LLMs), AI Chatbot |
| Pricing Model | Contact for Pricing | Paid |
| Monthly Visits | 28,786 | 234,678,639 |
| MoM Growth Rate | -5.1% | -9.6% |
| Primary Market | United States | United States |
| Direct Visits | 20,889 | 105,101,079 |
| Review Score | 4.4 | 4.8 |
| Saved Count | 0 | 144 |
| Supported Platforms | Website | Website |

## Inkeep

Inkeep is built around the idea that engineering and business teams should ship AI agents on one shared platform. It offers two surfaces that stay in sync: a no-code visual builder for business users and a TypeScript Agent SDK for developers. Because both write to the same agent definitions, a non-technical owner can tweak an agent in the builder while an engineer extends the same agent in code, without forking into separate implementations.

The product covers three main agent categories. Customer-facing assistants use unified search over your knowledge base and product to answer complex customer questions and query customer-specific information. Inkeep Coworker gives CX teams a personal assistant triggered from Slack or a support platform, gathering context from your CRM, billing, and other systems and proposing ready-to-approve answers with human approvals. Automation agents watch for webhooks, schedules, or external events to keep the knowledge base current, and coordination agents route complex work to specialist sub-agents. Agents can take real actions such as creating tickets, updating CRMs, generating content, and sending notifications through MCP tools.

Inkeep markets itself to support, documentation, product, and go-to-market teams that want AI agents they can trust, backed by governance, testing, reports, and connectors. It offers open-source components, and pricing is arranged through a demo rather than self-serve checkout.

**Pricing & Plans:** Contact for pricing. Inkeep routes prospects through a demo and does not advertise public self-serve tiers, so pricing depends on your requirements; talk to their team for a quote.

- **No-code visual builder:** Business teams create and own AI agents through a visual builder without writing code, defining triggers, sub-agents, and tools.
- **Developer Agent SDK:** Engineers build the same agents in TypeScript with an SDK that supports sub-agents, delegation, and MCP tools.
- **Two-way sync:** Builder and SDK write to shared agent definitions, so non-technical and technical teams can collaborate on the same agents.
- **Coworker agents:** CX assistants triggered from Slack or a support platform gather context from CRM and billing and propose human-approved answers.
- **Automation and orchestration:** Agents run on webhooks, schedules, or external events, route to specialist sub-agents, and take real actions via MCP.

**Strengths:** One platform where business and engineering teams build agents together with two-way sync; Covers customer-facing assistants, internal coworkers, and knowledge automation; Agents can take real actions through MCP tools and dedicated connectors; Open-source components and governance, testing, and reporting for enterprise trust

**Limitations:** Pricing is only available by contacting sales, so no public self-serve plans; The SDK and multi-agent orchestration assume some developer involvement; Better suited to teams with substantial documentation and support volume than to individuals

[Profile (Markdown)](https://openaitools.app/tool/inkeep.md)

## OpenAI Platform

While ChatGPT serves end users, openai.com and the OpenAI Developer Platform (developers.openai.com) provide the foundational API, SDKs, and enterprise infrastructure powering thousands of production AI applications worldwide. In late 2026, OpenAI's API catalog is anchored by the GPT-6 and GPT-6.1 model suite—all featuring a 1.05-million-token context window and up to 128K output tokens. The lineup spans GPT-6 Astra for frontier reasoning and mission-critical research, GPT-6.1 Sol for near-Astra intelligence at one-fifth the price, GPT-6.1 Terra for fast visual reasoning and computer use, and GPT-6 Luna for ultra-high-volume, low-latency tasks, alongside specialized models like `gpt-5.3-codex` and `gpt-6-astra-law`.

The OpenAI Platform has evolved well beyond basic chat completion endpoints. Through the unified `v1/responses` API, developers can orchestrate stateful multi-step agents equipped with built-in server-side tools—including live web search, vector file search, code interpreter sandboxes, and GUI computer use—without stitching together external orchestration frameworks. Every flagship model supports configurable reasoning effort (`none`, `low`, `medium`, `high`, `xhigh`, and `max`), strict JSON schema Structured Outputs, and multimodal image/audio inputs, while `gpt-live-1` powers per-second billed speech-to-speech voice agents.

OpenAI bills API usage on a transparent consumption model scaled across usage tiers (Build, Launch, and Grow, scaling up to 40M+ tokens per minute). In 2026, aggressive price cuts on the 6.x generation dropped entry-level intelligence on GPT-6 Luna to $0.10 per million input tokens and $0.50 per million output tokens, while GPT-6.1 Sol runs at $2/$10 and flagship GPT-6 Astra sits at $10/$50. Engineering teams can cut spend by 90% on repeated context using automatic Prompt Caching, save 50% on asynchronous workloads via the Batch API, and enforce regional data residency with a 10% compliance uplift.

**Pricing & Plans:** Usage-based pay-per-token API billing: GPT-6 Astra at $10/1M input and $50/1M output tokens; GPT-6.1 Sol at $2/1M input and $10/1M output; GPT-6.1 Terra at $1/1M input and $5/1M output; GPT-6 Luna at $0.10/1M input and $0.50/1M output; GPT-Live-1 voice at $0.05/minute; 90% discount on cached inputs and 50% off via Batch API.

- **GPT-6 & GPT-6.1 Model Lineup with 1.05M Context:** Spanning GPT-6 Astra ($10/$50 per MTok), GPT-6.1 Sol ($2/$10), GPT-6.1 Terra ($1/$5), and GPT-6 Luna ($0.10/$0.50), all with a 1,050,000-token context window and 128K max output.
- **Configurable Reasoning Effort Controls:** Tune thinking token budgets per API request across six granularity levels (`none`, `low`, `medium`, `high`, `xhigh`, `max`) to balance latency, accuracy, and cost.
- **Responses API & Native Computer Use Tools:** Combine model inference with hosted web search, file search, function calling, and autonomous GUI computer-use actions in a single stateful API call.
- **GPT-Live-1 Realtime Voice API:** Build ultra-low-latency multimodal voice agents billed per second ($0.05/minute) without rounding up to whole minutes.
- **90% Prompt Caching Discount & Batch API:** Cached input tokens bill at just 10% of standard input rates, while asynchronous 24-hour Batch API jobs cut both input and output token costs by 50%.

**Strengths:** 100-fold cost flexibility from GPT-6 Luna ($0.10/$0.50 per 1M tokens) up to frontier GPT-6 Astra ($10/$50 per 1M tokens); Unified 1.05M-token context window and 128K output limit across the entire flagship GPT-6 and GPT-6.1 family; 90% discount on cached input tokens and 50% Batch API discount dramatically reduce production inference bills; Industry-standard SDKs, Structured Outputs, and built-in Responses API tools minimize boilerplate agent code

**Limitations:** Long-context requests exceeding the standard window threshold trigger roughly 2x higher per-token billing rates; Flagship GPT-6 Astra ($10 input / $50 output per 1M tokens) is significantly more expensive than Claude Opus 5.5 ($4/$20) and Grok 4.7 ($2/$6); Regional data residency endpoints incur a 10% price uplift on models released after March 2026

[Profile (Markdown)](https://openaitools.app/tool/openai.md)

## Frequently Asked Questions

### How do Inkeep and OpenAI Platform compare in monthly traffic?

Inkeep has 28,786 monthly visits, while OpenAI Platform has 234,678,639. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Inkeep has a month-over-month growth rate of -5.1%; OpenAI Platform has -9.6%.

### How does pricing compare?

Inkeep: Contact for Pricing. Contact for pricing. Inkeep routes prospects through a demo and does not advertise public self-serve tiers, so pricing depends on your requirements; talk to their team for a quote. OpenAI Platform: Paid. Usage-based pay-per-token API billing: GPT-6 Astra at $10/1M input and $50/1M output tokens; GPT-6.1 Sol at $2/1M input and $10/1M output; GPT-6.1 Terra at $1/1M input and $5/1M output; GPT-6 Luna at $0.10/1M input and $0.50/1M output; GPT-Live-1 voice at $0.05/minute; 90% discount on cached inputs and 50% off via Batch API.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Google AI Studio](https://openaitools.app/tool/google-ai-studio) | 112,620,020 | +2% | Freemium | Provides direct API access to Google's Gemini models with generous free prototyping tiers, but lacks OpenAI's ecosystem breadth. | [.md](https://openaitools.app/tool/google-ai-studio.md) |
| 2 | [Qwen 4 (Alibaba Qwen4)](https://openaitools.app/tool/qwen-4) | 35,101,353 | -6.2% | Freemium | Alibaba Cloud's 4th-generation multimodal AI assistant and foundation model lineup (Qwen4-Max, Qwen4-Plus, Qwen4-Flash & open-weight Qwen4-27B) with 1M context. | [.md](https://openaitools.app/tool/qwen-4.md) |
| 3 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | Unifies hundreds of third-party models under a single API key, offering greater model choice than OpenAI's curated catalog. | [.md](https://openaitools.app/tool/openrouter-ai.md) |
| 4 | [BigModel](https://openaitools.app/tool/bigmodel) | 5,700,686 | -17% | Freemium | Provides developer APIs for Zhipu AI's proprietary GLM models, serving as an alternative enterprise foundation model stack. | [.md](https://openaitools.app/tool/bigmodel.md) |
| 5 | [Intercom](https://openaitools.app/tool/intercom-com) | 4,471,110 | +2.7% | Free Trial, Paid | AI-first customer service with a natively integrated AI agent | [.md](https://openaitools.app/tool/intercom-com.md) |
| 6 | [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Optimized for lightning-fast serverless execution of generative media and image models, rather than general text LLMs. | [.md](https://openaitools.app/tool/fal-ai.md) |
| 7 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Specializes in high-performance serverless inference and dedicated GPU clusters for open-source models, bypassing closed commercial restrictions. | [.md](https://openaitools.app/tool/together-ai.md) |
| 8 | [Crisp](https://openaitools.app/tool/crisp-chat) | 1,408,646 | +1.5% | Free Trial, Paid, Contact for Pricing, Free | AI-first customer support platform with a shared inbox built in | [.md](https://openaitools.app/tool/crisp-chat.md) |
| 9 | [Replicate AI](https://openaitools.app/tool/replicate-ai) | 904,038 | -8.4% | Paid | Focuses heavily on running and fine-tuning open-source vision and language models via simple APIs, unlike OpenAI's hosted closed models. | [.md](https://openaitools.app/tool/replicate-ai.md) |
| 10 | [Atlas Cloud](https://openaitools.app/tool/atlas-cloud) | 777,031 | -16.4% | Paid | One OpenAI-compatible API for 500+ image, video, audio, and LLM models | [.md](https://openaitools.app/tool/atlas-cloud.md) |

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Source: https://openaitools.app/compare/inkeep-vs-openai

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